Evolving Treatment Strategies for Inflammatory Breast Cancer: A Population-Based Survival Analysis
Bibliographic record
Abstract
PURPOSE: To determine if mastectomy (Mx) use, chemotherapy (CT) intensity, or treatment sequence of CT, radiation therapy (RT), and Mx have improved outcome for inflammatory breast cancer (IBC). PATIENTS AND METHODS: A retrospective analysis of 485 patients with IBC diagnosed in British Columbia between 1980 and 2000 analyzed locoregional relapse-free survival (LRFS) and breast cancer-specific survival (BCSS) by treatment intent and treatment received. Curative intent was defined as delivery of more than four cycles of anthracycline-based CT plus locoregional RT in patients without distant metastases. RESULTS: Median follow-up among survivors was 6.5 years. Median BCSS was 1.0 and 3.2 years for patients with distant metastases at diagnosis or those who were curatively treated, respectively. Among patients treated curatively (n = 308), there were no significant differences in LRFS or BCSS with timing of Mx before or after CT/RT, time between diagnosis and RT, or the sequence of RT and CT. Patients receiving more intensive CT had improved 10-year BCSS compared with standard CT (43.7% v 26.3%; P = .04). Ten-year LRFS for patients having Mx after CT, Mx before CT, and without Mx was 62.8%, 58.6%, and 34.4%, respectively (P = .0001); the corresponding 10-year BCSS was 36.9%, 19.9%, and 22.5%, respectively (P = .005). On multivariate analysis, Mx was associated with improved LRFS (P = .04). Independent prognostic factors for BCSS were menopausal status (P = .02), estrogen receptor status (P = .02), and CT type (P = .05). CONCLUSION: This retrospective analysis suggested that mastectomy, in conjunction with CT and RT, seemed to enhance locoregional control, whereas modern CT regimens seemed to improve BCSS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".